Universal data relationship inference engine

ABSTRACT

While a user is viewing content on a computer display, the universal data relationship inference engine presents related information from disparate data sources. A normalized index is maintained that indexes content to a set of standard taxonomy terms. The inference engine parses content being viewed by the user. If the content includes tags for some of the standard taxonomy terms, then the system may provide the user with the ability to view the related content that is indexed by the normalized index. If there are not taxonomy tags then the system may attempt to recognize non-standard taxonomy terms in the content in order to provide the user with related content. The inference engine may also identify related content by identifying synonyms to the taxonomy terms.

BACKGROUND OF THE INVENTION

It is often a goal of a business to have its employees perform theirdaily work at a higher level. For example, a business may desire thatits sales force, call center representatives, or professional servicesrepresentatives be more effective in their day-to-day businessactivities. One way to boost human performance is to provide people theinformation they need to do their jobs. Such information may includetraining, access to experts on specific topics, sample work products orother knowledge that is pertinent to helping the employee do his or herjob.

For example, a computer system may allow a call center representative toperform a search on support materials. Or the system may allow the callcenter representative access to a trouble ticket system for the purposeof discovering how similar problems have been solved in the past.Providing access to support materials is not without its problems. Acompany may have its content on too many different systems. This thenrequires a computer user looking for an answer to search each systemindividually. Or, a company may have its content stored in anunorganized fashion. While an answer may exist, the user may be unableto find the answer among the unorganized materials. Or the user may notknow how to properly navigate the computer system to find theinformation he or she needs or may not know how to formulate aneffective query to search for the information. These and other problemscan prevent people from performing at a higher level.

SUMMARY OF THE INVENTION

While a user is viewing content on a computer display, the universaldata relationship inference engine may present related information fromdisparate data sources. A normalized index may be maintained thatindexes content to a set of standard taxonomy terms. The inferenceengine may parse content being viewed by the user. If the contentincludes tags for some of the standard taxonomy terms, then the systemmay provide the user with the ability to view the related content thatis indexed by the normalized index. If there are not standard taxonomytags, then the system may attempt to recognize non-standard tags in thecontent or derive standard tags in order to provide the user withrelated content. The inference engine may also identify related contentby identifying synonyms to the taxonomy terms.

It is an objective of the invention to provide computer system userswith the ability to leverage content that is relevant to the user's taskat hand. It is another objective of the invention to provide highlyrelevant related information to a computer user. It is yet anotherobjective of the invention to provide related content in near proximityto the task being handled by a computer user. These and other objectivesare realized by embodiments of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart of one embodiment of the present invention.

FIG. 2 is a screen shot of a computer application in use by a computeruser.

FIG. 3 is a schematic diagram illustrating a feature of the embodimentof FIG. 1.

FIG. 4 is a flowchart of another embodiment of the present invention.

FIG. 5 is a schematic diagram of a feature of the present inventionthat, in the example, is accessible from the computer application ofFIG. 2.

DETAILED DESCRIPTION OF THE INVENTION

Aspects of the invention may be embodied in “A Universal DataRelationship Inference Engine” system, which is also referred to as theAUDRIE system for short. FIG. 1 is a flowchart that maps the majorsystem components in one embodiment of the AUDRIE system 100. As can beseen in FIG. 1, this embodiment of AUDRIE includes three subsystems,namely, the tag normalization subsystem 105, the index normalizationsubsystem 110 and the display subsystem 115.

FIG. 2 is a screen shot showing a primary computer application 205 aswell as reference support offered by AUDRIE 210 (shown within the dashedlines). The flowchart of FIG. 1 can be explained through reference tothis screen shot.

In step 120, a computer user may view new content. This content may bedisplayed while the user is accessing a web site, while she is running asoftware application (such as is shown in FIG. 2), etc. The contentbeing viewed 205 drives what reference support is offered by AUDRIE 210.In one embodiment of the invention, AUDRIE reacts to three contentscenarios. In the first scenario, the displayed content may beidentified as content that has already been tagged via a standardtaxonomy that is recognizable by the AUDRIE system. In the secondscenario, the displayed content may be managed by another applicationthat has its own taxonomy, such taxonomy already having been mapped toAUDRIE's standard taxonomy. In the third scenario, the viewed contentmay contain no tags or may be tagged with an unknown taxonomy. In thiscase, AUDRIE reads the content to discover which of the standardtaxonomy terms (or synonyms to terms) are contained in the content.

These three scenarios are handled in steps 125-145, which make upAUDRIE's Tag Normalization subsystem. In the embodiment shown in FIG. 1,AUDRIE first determines whether the content is tagged using arecognized, standard taxonomy (step 125). If so, then AUDRIE may parsethe standard tags in the content (step 130). If there are not standardtags, AUDRIE determines whether the content is based on a taxonomy thathas been previously mapped (step 135). If so, then AUDRIE may read thecontent's tags and use a database 150 to convert them to the mappedstandard tags (step 140). If the content does not follow a standardtaxonomy and if the content also does not include tags for which a knownmapping exists, then AUDRIE reads the content for standard taxonomyterms and synonyms (step 145). Reading screens for content is well knownin the art. For example, for web site content, it is well known that acomputer program can be designed to parse the underlying HTML code.

Through these three scenarios, AUDRIE's Tag Normalization subsystem 105compiles a list of normalized tags representing the type of contentbeing displayed to the user. AUDRIE's Display subsystem 115 handlesretrieving reference materials related to the content and presentingthese reference materials to the user. At step 155, AUDRIE searches anormalized index for the normalized tags for the current content todetermine which reference materials may be related to the content thatthe user is viewing. Although AUDRIE could present all of thesereference materials to the user, in one embodiment, AUDRIE deduces whichsubset of the materials might be most relevant to the displayed contentand displays it in standard categories (step 160). Then only this mostrelevant reference material is made available to the user.

Element 210 of FIG. 2 shows one embodiment of a toolbar provided for byAUDRIE. As shown, AUDRIE provides the user access to various types ofrelevant content. Based on the content being viewed 205, a set ofrelevant tasks may be presented 215 (such as wanting to set up a newcustomer, wanting to complete a skill assessment, etc.). Relevantknowledge reference materials 230 may also be available. AUDRIE may alsoenable access to relevant collaboration materials 235 or relevantexperts 240. The user may have access to relevant training 245 or tomaterials that support a relevant business process 250. Other relevantcomputer applications 255 as well as business intelligence 260 may bemade available through AUDRIE. Of course, these types of referencematerials are some of the many types that can be supported by AUDRIE.

The AUDRIE toolbar 210 may be configured to collapse and expandcategories of reference materials to save screen real estate. In theexample shown in FIG. 2, reference categories for which AUDRIE hasdetermined relevant content may have blinking indicators 220 while blankcategories have non-blinking indicators 225. By clicking on one of theblinking indicators 220, the user is able to expand the category fromjust the heading to the actual content within. For example, under theExperts category, FIG. 2 shows that AUDRIE has determined that JamesSmith, Sarah Martin and Erica Bayou can be contacted for expertiseregarding the type of content currently being displayed 205. AUDRIE mayenable additional reference materials to be presented or searched. InFIG. 2, each category expanded with content includes a “More” link. Forexample, in the Experts category, the user may click on this “More” linkto access a search feature shown in FIG. 5. This enables the user tofind reference materials that are outside of the short list of itemsdisplayed in the AUDRIE toolbar. For example, here the user is able tosearch for experts based on specific qualifications, such as a companyor sales process.

As has now been explained, AUDRIE's Tag Normalization subsystem 105determines the type of content being displayed to the user based oncertain tags. AUDRIE's Display subsystem 115 searches for the tags in anormalized index in order to present the most relevant referencematerials to the user. AUDRIE's Index Normalization subsystem 110, whichbuilds and maintains this normalized index will now be described.

Reference materials may be stored in a series of content sources 180.For example, as FIG. 3 explains, in order to populate the Expertscategory 240, AUDRIE may rely on such content sources 180 as a company'sHR employee directory 305, a database of CVs/resumes for the employees310 and a skills database 315. In the embodiment shown in FIG. 1, AUDRIEcreates an index 175 for each of these content sources. The index may bebased on keywords or tags in the content sources. AUDRIE may have abackground process 170 that builds these indexes 175. Much likeidentifying the type of content being displayed to the user, to buildthe indices this background process 170 may search the content sources180 for standard tagging or for tagging that has been mapped to thestandard tags. The process 170 may also look for standard taxonomy termsor synonyms of these terms in the content sources. Each content sourceindex 175 may be combined to form a consolidated index 165. It is thisconsolidated index that AUDRIE's Display subsystem 115 may search todetermine the relevant reference materials to make available to theuser.

FIG. 3 also illustrates the concept of mapping non-standard taxonomies.FIG. 3 illustrates that taxonomies exist outside of AUDRIE. For example,a company may rely on a pre-existing expertise taxonomy to structuredata about its employees. AUDRIE may map this expertise taxonomy 320 toits standard taxonomy to interface with the various HR content sources325.

The foregoing description addresses embodiments encompassing theprinciples of the present invention. The embodiments may be changed,modified and/or implemented using various types of arrangements. Thoseskilled in the art will readily recognize various modifications andchanges that may be made to the invention without strictly following theexemplary embodiments and applications illustrated and described herein,and without departing from the scope of the invention, which is setforth in the following claims. For example, the AUDRIE system describedabove provides for analyzing content being viewed by the user in threeways, namely, looking for standard tags in the content, looking fornon-standard tags that have been mapped, and then looking for recognizedterms and synonyms. One skilled in the art will recognize that theAUDRIE system can be developed in differing embodiments. For example,FIG. 4 shows a non-tagged version of AUDRIE that is also within thescope of the present invention.

What is claimed is:
 1. A computer-implemented method for presenting, toa user of a computer, reference information related to content beingviewed by the computer user, the computer including a processor andmemory, and the method comprising steps performed by the computer of:identifying, by the processor, taxonomy tags and taxonomy terms in theviewed content, the step of identifying comprising: (a) determiningwhether the viewed content contains standard taxonomy tags, recognizednon-standard taxonomy tags, non-recognized taxonomy tags, or no tags;(b) determining whether the viewed content contains standard taxonomyterms or non-standard taxonomy terms, wherein if the viewed contentcontains non-recognized taxonomy tags or no tags, then the viewedcontent is read to determine any standard taxonomy terms contained inthe viewed content; and (c) compiling a standardized list comprising:ones of the determined standard taxonomy terms that are relevant to theviewed content; ones of the determined non-standard taxonomy terms thatare relevant to the content, the determined non-standard taxonomy termsbeing mapped to the determined standard taxonomy terms when thedetermined non-standard taxonomy terms are synonyms to the determinedstandard taxonomy terms; the determined standard taxonomy tags; and thedetermined recognized non-standard taxonomy tags, the determinedrecognized non-standard taxonomy tags being converted to standardtaxonomy tags; creating, by the processor, a normalized standardizedtaxonomy index, wherein the step of creating comprises: (a) locatingtaxonomy terms and taxonomy tags contained in a plurality of contentfiles from a plurality of disparate content sources; (b) building forthe plurality of content files an index of the located taxonomy termsand taxonomy tags; and (c) consolidating the built indices into aconsolidated index stored on a database; and automatically displaying,by the processor, related content, based on the standardized list andthe normalized standardized taxonomy index, to the computer user;wherein the step of displaying comprises: (a) parsing the viewed contentfor a plurality of taxonomy terms or tags from the standardized list;(b) searching, unprompted by the user, the normalized standardizedtaxonomy index for at least one of the plurality of taxonomy terms ortags from the standardized list; (c) retrieving related content based onthe searching; and (d) displaying the related content to the computeruser.
 2. The method of claim 1 further comprising: mapping, by theprocessor, the taxonomy terms to standard taxonomy terms when thetaxonomy terms are synonyms to standard taxonomy terms.
 3. The method ofclaim 1, wherein a standardized tag index indexes related content fromthe plurality of disparate content sources.
 4. A computer-implementedmethod for presenting, to a user of a computer, reference informationfrom a plurality of content sources related to content being viewed bythe computer user, the computer including a processor and memory, andthe method comprising steps performed by the computer of: parsing, bythe processor, the viewed content for a plurality of standardizedtaxonomy terms, wherein if the viewed content contains non-recognizedtaxonomy tags or no tags, then the viewed content is parsed to determineany standard taxonomy terms contained in the viewed content; searching,unprompted by the user, by the processor, a normalized standardizedtaxonomy term index for at least one of the plurality of standardizedtaxonomy terms for determining related content; retrieving, by theprocessor, the related content; and automatically displaying, by theprocessor to the computer user, the related content.
 5. The method ofclaim 4, further comprising: mapping, by the processor, non-standardtaxonomy terms to standard taxonomy terms when the non-standard taxonomyterms are synonyms to standard taxonomy terms.
 6. The method of claim 4,wherein the normalized standardized index indexes related content from aplurality of content sources.
 7. The method of claim 4, wherein the stepof displaying displays the related content on a display device that isalso displaying the viewed content.
 8. A computer-implemented method foridentifying standardized taxonomy terms in content being viewed by auser of a computer, the computer including a processor and memory, andthe method comprising steps performed by the computer of: determining,by the processor, whether the viewed content contains standard taxonomytags or recognized non-standard taxonomy tags; compiling, by theprocessor, a list comprising standardized taxonomy terms relevant to theviewed content, wherein compiling comprises: (a) parsing the viewedcontent for a plurality of standard taxonomy terms and non-standardtaxonomy terms, wherein the non-standard taxonomy terms are synonyms ofstandard taxonomy terms and the plurality of standard taxonomy terms arestored in a database; (b) standardizing a plurality of standard taxonomytags and recognized non-standard taxonomy tags by mapping recognizednon-standard taxonomy tags to standard taxonomy tags stored in adatabase; and (c) reading the viewed content to determine any standardtaxonomy terms contained in the viewed content if the viewed contentcontains non-recognized taxonomy tags or no tags; searching, unpromptedby the user, by the processor, a normalized standardized taxonomy termindex for at least one of the standardized taxonomy terms fordetermining related content; retrieving, by the processor, the relatedcontent; and automatically displaying the related content, by theprocessor, to the user.
 9. The method of claim 8, wherein the step ofcompiling comprises: identifying, by the processor, a plurality ofstandard taxonomy terms for the viewed content by comparing words in theviewed content to standardized taxonomy terms stored in a database,wherein the standardized taxonomy terms comprise standard andnon-standard taxonomy terms and the non-standard taxonomy terms aresynonyms for the standard taxonomy terms.
 10. The method of claim 8,further comprising: mapping, by the processor, the non-standard taxonomyterms to standard taxonomy terms.
 11. A computer-implemented method forcreating a normalized standardized tag index for use in presenting, to auser of a computer, information from a plurality of sources that isrelated to content being viewed by the computer user, the computerincluding a processor and memory and the method comprising stepsperformed by the computer of: locating, by the processor: standard andnon-standard taxonomy terms contained in a plurality of content filesfrom a plurality of disparate sources, based on identified standard andnon-standard taxonomy terms in the viewed content; and standard andnon-standard taxonomy tags attached to a plurality of content files froma plurality of disparate content sources, based on identified standardand non-standard taxonomy tags attached to the viewed content, whereinif the viewed content contains non-recognized taxonomy tags or no tags,then the viewed content is read to locate any standard taxonomy termscontained in the content; building, by the processor for the pluralityof content files, an index of the located taxonomy terms and taxonomytags; consolidating, by the processor, the built indices into aconsolidated index stored on a database; searching, unprompted by theuser, by the processor, the consolidated index for content related tothe viewed content; and automatically displaying, by the processor,content related to the viewed content.
 12. The method of claim 11,wherein the step of consolidating comprises: mapping, by the processor,one or more of the taxonomy terms to standard taxonomy terms when theone or more of the taxonomy terms are synonyms to standard taxonomyterms.
 13. The method of claim 11, wherein the consolidated indexindexes related content from a plurality of content sources.